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Sovereign’s Capital
Sovereign’s Capital
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companies
782
Jobs

Lead Data Scientist (Dispatch)

Grab

Grab

Data Science
Singapore
Posted on Friday, June 21, 2024

Company Description

About Grab and our workplace

Grab is Southeast Asia's leading superapp. We are dedicated to improving the lives of millions of users across the region by providing them everyday services such as deliveries, mobility, financial services, enterprise services and others. More than that, we provide the opportunity for them to have a better life. And that aspiration starts inside Grab because we believe in a seamless blend of work and home life, making every aspect of life better for all.

Guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles—the 4Hs: Heart, Hunger, Honour and Humility—we work to create economic empowerment for the people of Southeast Asia. With our unwavering commitment to our values, we believe that we're more than a service provider; we're agents of positive change.

Job Description

Get to know our Team:

Grab's Fulfilment-Dispatch Data Science team works on challenging and fascinating problems surrounding Grab's allocation capabilities — ensuring our passengers, driver-partners, consumers and merchants enjoy a reliable fulfilment experience.

Get to know the role:

  • Build, deploy and own production-grade models and services as they serve millions of requests every day
  • Design, develop and deploy predictive models to enable dispatch decisions that adapt to changing market conditions
  • Understand business needs, identify areas for investigation, translate them to technical problems to be solved

The day-to-day activities:

  • Research, analyze high-volume high-velocity data, build quick prototypes, and engineer them into production
  • Design data pipelines and conduct experiments to measure the impact of your work
  • Effectively communicate results and their implications to business/product stakeholders

Qualifications

The must haves:

  • PhD or Master's degree in Computer Science, Electrical/Computer Engineering, Industrial & Systems Engineering, Operations Research, Mathematics/Statistics, Transportation Engineering, or related technical disciplines with 3+ years of DS work at a technology company; or equivalent experience
  • Strong Machine Learning fundamentals:
  • Understanding of machine learning algorithms and their ecosystem (data, model persistence, tooling, development lifecycle)
  • Experience in developing production-grade ML systems including exploratory analysis, feature engineering, developing data pipelines, observability and maintenance etc.
  • Strong aptitude in statistics and large-scale data analytics:
  • Understanding of probability and statistics (e.g. hypothesis testing, modeling distributions / regressions, Bayesian statistics etc)
  • Experienced in running live experiments (A/B tests, randomized controlled trials) and analyzing their results
  • Experienced with relational databases, SQL, and distributed computing frameworks (Spark, Kafka stream processing)
  • Strong software development skills:
  • Proficient in Python. Skill in Golang, Scala or Rust is an advantage.
  • Familiar with Git-based source control, code reviews, test-driven development, cloud-based development (AWS/Azure)
  • Self-motivated, independent learner, and willing to share knowledge with the team
  • Detail-oriented and efficient time manager in a dynamic working environment
  • Able to communicate well in English both verbally and in written communication, as well as convey data insights and results with effective visualizations.

Nice to have:

  • Experience in working with geospatial/mobility/logistics data
  • Experience in designing probabilistic models at scale in production
  • Familiar with modern data pipeline and warehousing stacks (e.g. Hive, Pinot, Airflow, Presto/Trino etc)
  • Expertise in any of these specialized domains: graph theory/processing, optimization of stochastic problems, agent-based simulation, adaptive control, reinforcement learning
  • Experience with designing, deploying and maintaining microservices (e.g. on Docker / Kubernetes) to serve production models is a big plus

Additional Information

Benefits at Grab:

We care deeply about your well-being and are committed to supporting you every step of the way. Here are some of the global benefits we offer:

  • Protect and provide for your loved ones with peace of mind, knowing we have your back with Term Life Insurance and comprehensive Medical Insurance.
  • Craft a benefits package that suits your unique needs and aspirations with GrabFlex, because we believe in empowering you to thrive.
  • Embrace the magic of new life and create lasting memories with your family through Maternity and Paternity Leave.
  • Life can be overwhelming, but you're never alone. Our confidential Grabber Assistance Programme is here to guide and uplift you and your loved ones through life's challenges.
  • Your well-being is our priority. Benefit from our holistic well-being initiatives through Wellbeing@Grab, including health programmes, informative webinars, and vibrant carnivals.
  • Achieve a harmonious work-life balance with our FlexWork arrangements, allowing you to adapt and thrive in your personal and professional life.

We've got many different benefits hyper localised in each country. Speak to your recruiter during your interview to find out more.

What we stand for at Grab:

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique. If you require accommodations to fully participate in the recruitment process, you are encouraged to include your request(s) when applying.

We deliver the greatest impact and ideas when we bring together diverse perspectives. It is what enables us to spread opportunities to Grabbers and our partners. It's not a box-ticking exercise; it's who we are.